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STUDY DESIGNS: case control, cohort and qualitative

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The Case Control Study: Design

The case control study: design3

Advantages

Efficient for studies of rare diseases and diseases with long latent periods

Cheap, simple, quick (in comparison to cohorts)

Can examine multiple exposures – generate hypotheses

Sometimes the only practical option (e.g. where long latent period between exposure and disease)

Disadvantages

There are many!

Can study only one outcome

Notorious for being prone to bias:

Sampling/selection bias – selection of cases and controls

Observation and recall bias

Not good for rare exposures

The temporal sequence between exposure and disease may be difficult to determine.

As with all studies, confounding

Selecting cases

Need a clear case definition and source

Incident or prevalent cases?

Cases selected for a study should be representative of all cases of the disease in the population.

Should be a random sample of all patients with the disease

This is difficult!: many cases not diagnosed or misdiagnosed

A hospital sample in some diseases may be very different from a community sample

Selecting controls

Controls are used to estimate the prevalence of exposure in the population which gave rise to the cases.

The ideal control group would comprise a random sample from the general population that gave rise to the cases.

Controls should meet all the criteria for cases, apart from having the disease itself; but they should have the potential to develop it

Recruiting more than one control per case may improve the statistical power of the study (up to 4 controls per case)

Selecting controls

Convenience sample

Matched sample

Using two or more control groups

Using population base sample e.g. from registers

Selecting controls: matching

Matching – Some studies are matched to select cases/controls who are as similar as possible e.g on age, ethnicity etc

Difference between cases and controls therefore cannot be a result of differences in the matching variables – for example, to take age into account

Can be useful in small samples – as we might not have sufficient subjects to adjust for several variables at once.

Difficult/complicated to match on too many factors.... In a large study with many variables it is easier to take an unmatched control group and adjust in the analysis for the variables on which we would have matched, using ordinary regression methods.

Important not to match on basis of risk factor of interest / too many factors – ‘overmatching’ may make the controls unrepresentative and underestimate the true difference

Case control studies and the odds ratio

Estimates the strength of association between an exposure and an outcome

Does not calculate relative risk as retrospective

Does not give incidence/prevalence – unless all cases in a population are included

The odds ratio is a measure of the odds of exposure in the cases, compared to the odds of exposure in the control group.

OR: 2 by 2 table

OR = (a/c)/(b/d)

Imaginary worked example – Cats and schizophrenia

Imaginary example– are cats associated with schizophrenia?

Odds of exposure in the cases: 80/20 = 4

Odds of exposure in the controls: 100/300 = 0.33

Odds ratio: 4/0.33 = 12.12

So……the odds of having had a cat as a child in the group with schizophrenia were over 12 times the odds of having had a cat as a child in the control group –

Or those with schizophrenia were over 12 times more likely to have had a cat as a child….

Why might we get this result?

Feline bias

Selection bias

Cases recruited through a charity that runs ‘pet experiences’ for people with mental illness

Controls were a hospital sample recruited from an allergy clinic

Both of these would spuriously increase estimate of effect

Recall bias

Are those with schizophrenia more likely to remember/report having had a cat – particularly if aware of hypothesis in question

Cohort studies

Cohort study design

Usually prospective; but can be retrospective

A prospective cohort

Prospective and retrospective cohort

Cohort studies may be prospective or retrospective, but both types define the cohort on the basis of exposure, not outcome.

Prospective cohort studies – participants are identified and followed up over time until the outcome of interest has occurred, or the time limit for the study has been reached. A temporal relationship between exposure and outcome can be established.

Retrospective cohort studies – exposure and outcome have already occurred at the start of the study. Pre-existing data, such as medical notes, can be used to assess any causal links, so lengthy follow-up is not required.

Sources of bias in cohort studies

Differential misclassification: can lead to an over- or underestimate of the effect between exposure and outcome.

Losses to follow up : degree to which losses to follow up are related to either exposure or outcome can lead to serious bias in the measurement of effect of exposure and outcome.2

Cohort studies in psychiatry: example

Andreasson et al: cannabis consumption and development of schizophrenia in a cohort of 45,570 Swedish conscripts4.

Relative risk in cohort studies

Analysis

Riskexp = a / (a+c) (divide by total exposed)

Riskunexp = b / (b+d) (divide by total unexposed)

Estimate relative risk = Riskexp / Riskunexp

Indicates increased/decreased risk of disease assoc with exp:

RR = 1 – risk is same in exposed and unexposed groups

RR > 1 – risk is greater in exposed group

RR < 1 – reduction in risk in exposed group

Example: relative risk from Swedish conscript cohort study4

Coffee and exam questions

Qualitative studies

Answers questions such as:

What is X & how does X vary in diff circumstances & why?

Not ‘how big is X or how many X’s are there?

Concerned withmeanings people attach to their experience of social world & how make sense of world

Uses of qualitative research

Preliminaryto quantitative research

Helps ensure validity of data obtained

E.g. interviews to inform a survey

To validate quantitative research or provide a diff perspective on same social phenomena

Used independently to uncover social processes or access areas of social life not amenable to quantitative research

Address the 'gap' between evidence-based approaches based on the findings of randomised control trials and the practice of clinical decision-making in individual cases

Qualitative vs. quantitative

Qualitative research methods: data gathering

Interviews

Focus groups

Observational/ethnographic

Interviews

Structured

Semi-structured

Depth interviews

Consider: recording

Reflexivity

Note on Reflexivity5

The researcher is not a neutral/mechanical tool

The researcher is not doing an experiment in which she/he sets the agenda

The person/people the researcher talks to are not inanimate objects, they also have agency and may try to set the agenda themselves

All social research, especially qualitative social research, hinges on social relationships:

They are affected by interpersonal dynamics and

The researcher AND researched 'co-produce' social encounters.

Reflexivity is reflecting, or thinking critically, carefully, honestly and openly, about the research experience and process.

Focus groups

Strengths

Help to identify group norms/cultural values

Group processes can help people to explore and clarify their views in ways that may be less easily accessible in interview

Can encourage participation from those reluctant to be interviewed

Can encourage contributions from people who feel have nothing to say

Weaknesses

Not easy option - data generated can be complex

Potential issues with confidentiality, or with ‘sensitive’ topics

Observational/ethnographic

Instead of asking questions about behaviour – the researcher systematically watches people and events to observe everyday behaviours and relationships

Aspires to be ‘naturalistic’ in that people are studied in situ with as little interference by the researcher as is feasible and ethical

Covert or overt

Participant or non-participant

Observational/ethnographic

Choice of setting is purposive

Consider characteristics of researcher, group and setting

Male, female

Young, old

Naïve or experienced

Accepted by group but don’t ‘go native’!

Ethical issues

Covert research roles must be justified

Recording observational data

Relies on researcher acting as research instrument and documenting the world they observe

Good memory

Clear and detailed recording

Jotted notes

Sift, decode and make sense of data to make meaningful

Sampling in qualitative research

Often a smaller sample size

Rich in detail

Phenomenon only needs to appear once

Not describing incidence/prevalence or statistical significance

Quantitative research uses probability sampling

Qualitative research uses non-probability sampling

not representative samples

findings cannot be generalised to the whole study population from which the sample was taken.

the people in the study population do not each have an equal chance of being selected.

Sampling in qualitative research

Purposive sampling

individual participants are selected deliberately for their specific characteristics that are of importance to the study

Quota based sampling

A quota is a defined number that must be included in a sample :ensures that a certain number of subjects from different subgroups with specific characteristics appear in the sample, so that all these characteristics are represented.

Snowball sampling

Useful for hard-to-reach groups/populations

Start with one or two contacts, ask for referrals/recommendations etc

Theoretical sampling: sampling related to previously developed hypotheses or theories

Analysing qualitative data (1)

Data preparation

Nature and scale of qualitative data

Transcription

Notes made during observation have to be turned into detailed descriptive accounts